{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import xlwings as xw\n",
    "df = pd.read_excel('互联网公司股票.xlsx')\n",
    "xw.view(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "import xlwings as xw"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "wb = xw.Book(\"互联网公司股票.xlsx\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'互联网公司股票.xlsx'"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wb.name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Sheets([<Sheet [互联网公司股票.xlsx]Sheet1>])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wb.sheets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "sheet = wb.sheets['Sheet1']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Sheet [互联网公司股票.xlsx]Sheet1>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sheet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>日期</th>\n",
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       "    </tr>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-10-03</td>\n",
       "      <td>BIDU</td>\n",
       "      <td>104.32</td>\n",
       "      <td>102.35</td>\n",
       "      <td>104.73</td>\n",
       "      <td>101.15</td>\n",
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       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-10-02</td>\n",
       "      <td>BIDU</td>\n",
       "      <td>102.62</td>\n",
       "      <td>100.85</td>\n",
       "      <td>103.24</td>\n",
       "      <td>99.5</td>\n",
       "      <td>2.69</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
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       "      <td>102</td>\n",
       "      <td>102.8</td>\n",
       "      <td>103.26</td>\n",
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       "      <td>1.78</td>\n",
       "      <td>-0.01</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-10-03</td>\n",
       "      <td>BABA</td>\n",
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       "      <td>166.65</td>\n",
       "      <td>170.18</td>\n",
       "      <td>165</td>\n",
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       "      <td>0.02</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
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       "      <td>166.88</td>\n",
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       "    <tr>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2019-10-03</td>\n",
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       "      <td>0.02</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2019-10-02</td>\n",
       "      <td>IQ</td>\n",
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       "      <td>15.85</td>\n",
       "      <td>15.87</td>\n",
       "      <td>15.12</td>\n",
       "      <td>8.1</td>\n",
       "      <td>-0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2019-10-01</td>\n",
       "      <td>IQ</td>\n",
       "      <td>15.92</td>\n",
       "      <td>16.14</td>\n",
       "      <td>16.22</td>\n",
       "      <td>15.5</td>\n",
       "      <td>11.65</td>\n",
       "      <td>-0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2019-10-03</td>\n",
       "      <td>JD</td>\n",
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       "      <td>28.11</td>\n",
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       "      <td>27.82</td>\n",
       "      <td>8.77</td>\n",
       "      <td>0.03</td>\n",
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       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2019-10-02</td>\n",
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       "      <td>2019-10-01</td>\n",
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       "      <td>27.97</td>\n",
       "      <td>10.64</td>\n",
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       "            日期    公司      收盘      开盘       高       低    交易量     涨跌幅\n",
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       "1   2019-10-02  BIDU  102.62  100.85  103.24    99.5   2.69   0.01 \n",
       "2   2019-10-01  BIDU     102   102.8  103.26     101   1.78  -0.01 \n",
       "3   2019-10-03  BABA  169.48  166.65  170.18     165  10.39   0.02 \n",
       "4   2019-10-02  BABA  165.77  162.82  166.88   161.9   11.6   0.00 \n",
       "5   2019-10-01  BABA  165.15  168.01  168.23  163.64  14.19  -0.01 \n",
       "6   2019-10-03    IQ   16.06   15.71   16.38   15.32  10.08   0.02 \n",
       "7   2019-10-02    IQ   15.72   15.85   15.87   15.12    8.1  -0.01 \n",
       "8   2019-10-01    IQ   15.92   16.14   16.22    15.5  11.65  -0.01 \n",
       "9   2019-10-03    JD    28.8   28.11   28.97   27.82   8.77   0.03 \n",
       "10  2019-10-02    JD   28.06      28   28.22   27.53   9.53   0.00 \n",
       "11  2019-10-01    JD   28.19   28.22   28.57   27.97  10.64   0.00 "
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     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
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    "sheet.range('A1').options(pd.DataFrame, header=1, index=False, expand='table').value"
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   "cell_type": "code",
   "execution_count": 29,
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   "outputs": [
    {
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